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Estimating physical assistance need using a musculoskeletal model.

Marc G Carmichael¹, Dikai Liu

¹Centre for Autonomous Systems, University of Technology, Sydney 2007, Australia. marc.g.carmichael@student.uts.edu.au

IEEE Transactions on Bio-Medical Engineering

|February 6, 2013

Summary

This study introduces a new musculoskeletal model (MM) approach for estimating physical assistance needs in tasks. It calculates the gap between operator strength and task demands, improving assistance-as-needed (AAN) paradigms.

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Area of Science:

Robotics
Biomechanics
Human-Computer Interaction

Background:

Physical assistance technologies require task- and user-specific adaptation.
Current assistance-as-needed (AAN) methods rely on empirical, performance-based estimations.
Existing methods necessitate repeated task observation to determine assistance levels.

Purpose of the Study:

To present a novel approach for estimating operator assistance needs using a musculoskeletal model (MM).
To develop a new AAN paradigm based on the difference between operator strength capability and task demands.

Main Methods:

Utilized an upper limb musculoskeletal model (MM) to define operator capabilities at the muscular level.
Employed an optimization model to estimate operator strength capability.

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Calculated task strength requirements using a task model.

Main Results:

Developed a new AAN paradigm based on the strength gap between the operator and the task.
Demonstrated the model's ability to estimate the impact of limb pose, load direction, and muscle impairments on task performance.

Conclusions:

The proposed MM-based approach offers a more precise method for determining physical assistance needs.
This model advances AAN paradigms in areas like robotic rehabilitation by accounting for individual capabilities and task specifics.